47 citations · 153 across the 19 of their papers we have counts for
7 papers · 1 filter
Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting
Xinyan Guan, Yanjiang Liu, Hongyu Lin +4
Incorporating factual knowledge in knowledge graph is regarded as a promising approach for mitigating the hallucination of large language models (LLMs). Existing methods usually on…
Offline Pseudo Relevance Feedback for Efficient and Effective Single-pass Dense Retrieval
Xueru Wen, Xiaoyang Chen, Xuanang Chen +2
Dense retrieval has made significant advancements in information retrieval (IR) by achieving high levels of effectiveness while maintaining online efficiency during a single-pass r…
Defense of Adversarial Ranking Attack in Text Retrieval: Benchmark and Baseline via Detection
Xuanang Chen, Ben He, Le Sun +1
Neural ranking models (NRMs) have undergone significant development and have become integral components of information retrieval (IR) systems. Unfortunately, recent research has un…
Understanding Differential Search Index for Text Retrieval
Xiaoyang Chen, Yanjiang Liu, Ben He +2
The Differentiable Search Index (DSI) is a novel information retrieval (IR) framework that utilizes a differentiable function to generate a sorted list of document identifiers in r…
Towards Imperceptible Document Manipulations against Neural Ranking Models
Xuanang Chen, Ben He, Zheng Ye +2
Adversarial attacks have gained traction in order to identify potential vulnerabilities in neural ranking models (NRMs), but current attack methods often introduce grammatical erro…
Influence of External Information on Large Language Models Mirrors Social Cognitive Patterns
Ning Bian, Hongyu Lin, Peilin Liu +5
Social cognitive theory explains how people learn and acquire knowledge through observing others. Recent years have witnessed the rapid development of large language models (LLMs),…
ChatGPT is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language Models
Ning Bian, Xianpei Han, Le Sun +5
Large language models (LLMs) have made significant progress in NLP. However, their ability to memorize, represent, and leverage commonsense knowledge has been a well-known pain poi…